MATH 225N Week 6 Discussion: Confidence Intervals
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$15.00
| Institution | MATH 225N Statistical Reasoning for the Health Sciences |
| Contributor | Brianna |
Confidence Intervals
In everyday terms, a
confidence interval is the range of values around a sample statistic (such as
mean or proportion) within which clinicians can expect to get the same results
if they repeat the study protocol or intervention, including measuring the same
outcomes the same ways. As you ask yourself, "Will I get the same results
if I use this research?", you must address the precision of study
findings, which is determined by the Confidence Interval. If the CI around the
sample statistic is narrow, you can be confident you will get close to the same
results if you implement the same research in your practice.
Consider the following
example. Suppose that you did a systematic review of studies on the effect of
tai chi exercise on sleep quality, and you found that tai chi affected sleep
quality in older people. If, according to your study, you found the lower
boundary of the CI to be .49, the study statistic to be 0.87, and the upper
boundary to be 1.25, this would mean that each end limit is 0.38 from the
sample statistic, which is a relatively narrow CI.
(UB + LB)/2 = Statistic
[(1.25 + .49)/2 = .87]
Keep in mind that a mean
difference of 0 indicates there is no difference; this CI does not contain 0. Therefore,
the sample statistic is statistically significant and unlikely to occur by
chance.
Because this was a systematic
review, and tai chi exercise has been established from the studies you assessed
as helping people sleep, based on the sample statistics and the CI, clinicians
could now use your study and confidently include tai chi exercises among
possible recommendations for patients who have difficulty sleeping.
Now you can apply your
knowledge of CIs to create your own studies and make wise decisions about whether
to base your patient care on a particular research finding.
Initial Post Instructions
Thinking of the many
variables tracked by hospitals and doctors' offices, confidence intervals could
be created for population parameters (such as means or proportions) that were
calculated from many of them.
Choose a topic of study that
is tracked (or you would like to see tracked) from your place of work. Discuss
the variable and parameter (mean or proportion) you chose, and explain why you
would these to create an interval that captures the true value of the parameter
of patients with 95% confidence.
Consider the following:
How would changing the confidence interval to 90% or 99% affect the study? Which of these values (90%, 95%, or 99%) would best suit the confidence level according to the type of study chosen? How might the study findings be presented to those in charge in an attempt to affect change at the workplace?
| Instituition / Term | |
| Term | Summer 2020 |
| Institution | MATH 225N Statistical Reasoning for the Health Sciences |
| Contributor | Brianna |
